Spatial Data Analysis: Theory and Practice provides a broad-ranging treatment of the field of spatial data analysis. It begins with an overview of spatial data analysis and the importance of location (place, context and space) in scientific and poli
Bayesian methods are increasingly becoming attractive to researchers in many fields. Econometrics, however, is a field in which Bayesian methods have had relatively less influence. A key reason for this absence is the lack of a suitable advanced und
Ken Binmore is an outstanding exponent of game theory. His many books are written in a delightfully fresh and engaging style, as is this one. Enjoy! Playing for Real will sell into advanced undergraduate courses in game theory, primarily those in ec
This book aims at introducing Ph.D. students and professional economists to the theory of contracts. It originated in graduate-level courses I gave at Stanford University and at ENSAE (Ecole National de la Statistique et de VAdministration Economiqu
Spatial Data Analysis: Theory and Practice provides a broad-ranging treatment of the field of spatial data analysis. It begins with an overview of spatial data analysis and the importance of location (place, context and space) in scientific and poli
Fisher was one of America’s greatest mathematical economists. This book is still used a textbook and is an outstanding example of clearly written economic theory.
Review "Deirdre McCloskey's Economical Writing, originally aimed to help economists write better, is in this second edition clearly a book that should be read by scholars in every field. Her thirty-one rules, offered with wit and delightful brevity,
Preface Python for Informatics: Remixing an Open Book It is quite natural for academics who are continuously told to “publish or perish” to want to always create something from scratch that is their own fresh creation. This book is an experiment in
Data mining is well on its way to becoming a recognized discipline in the overlapping areas of IT, statistics, machine learning, and AI. Practical Data Mining for Business presents a user-friendly approach to data mining methods, covering the typica
In this book, we develop a Machine Learning framework to predict economic growth and the likelihood of recessions. In such a framework, different algorithms are trained to identify an internally validated set of correlates of a particular target wit
The importance of having basic knowledge of computational methods continues to increase for those working in the nancial services industry. Computational nance theory has developed along with advancements in computing technology. The objective of th
Data mining is well on its way to becoming a recognized discipline in the overlapping areas of IT, statistics, machine learning, and AI. Practical Data Mining for Business presents a user-friendly approach to data mining methods, covering the typica
